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Establishment of a prognosis predictive model for liver cancer based on expression of genes involved in the ubiquitin-proteasome pathway.
Li, Hua; Ma, Yi-Po; Wang, Hai-Long; Tian, Cai-Juan; Guo, Yi-Xian; Zhang, Hong-Bo; Liu, Xiao-Min; Liu, Peng-Fei.
Affiliation
  • Li H; Department of Endoscopy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.
  • Ma YP; Department of Critical Care Medicine, Dingzhou City People's Hospital, Dingzhou 073000, Hebei Province, China.
  • Wang HL; Department of Oncology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, Tianjin 300120, China.
  • Tian CJ; Tianjin Marvel Medical Laboratory, Tianjin Marvelbio Technology Co., Ltd, Tianjin 300180, China.
  • Guo YX; Department of Intelligent Technology, Tianjin Yunquan Intelligent Technology Co., Ltd, Tianjin 300381, China.
  • Zhang HB; Tianjin Marvel Medical Laboratory, Tianjin Marvelbio Technology Co., Ltd, Tianjin 300180, China.
  • Liu XM; Department of Oncology, Tianjin Huanhu Hospital, Tianjin 300350, China.
  • Liu PF; Department of Oncology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, Tianjin 300120, China. liupengfeitj@163.com.
World J Clin Oncol ; 15(3): 434-446, 2024 Mar 24.
Article in En | MEDLINE | ID: mdl-38576590
ABSTRACT

BACKGROUND:

The ubiquitin-proteasome pathway (UPP) has been proven to play important roles in cancer.

AIM:

To investigate the prognostic significance of genes involved in the UPP and develop a predictive model for liver cancer based on the expression of these genes.

METHODS:

In this study, UPP-related E1, E2, E3, deubiquitylating enzyme, and proteasome gene sets were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, aiming to screen the prognostic genes using univariate and multivariate regression analysis and develop a prognosis predictive model based on the Cancer Genome Atlas liver cancer cases.

RESULTS:

Five genes (including autophagy related 10, proteasome 20S subunit alpha 8, proteasome 20S subunit beta 2, ubiquitin specific peptidase 17 like family member 2, and ubiquitin specific peptidase 8) were proven significantly correlated with prognosis and used to develop a prognosis predictive model for liver cancer. Among training, validation, and Gene Expression Omnibus sets, the overall survival differed significantly between the high-risk and low-risk groups. The expression of the five genes was significantly associated with immunocyte infiltration, tumor stage, and postoperative recurrence. A total of 111 differentially expressed genes (DEGs) were identified between the high-risk and low-risk groups and they were enriched in 20 and 5 gene ontology and KEGG pathways. Cell division cycle 20, Kelch repeat and BTB domain containing 11, and DDB1 and CUL4 associated factor 4 like 2 were the DEGs in the E3 gene set that correlated with survival.

CONCLUSION:

We have constructed a prognosis predictive model in patients with liver cancer, which contains five genes that associate with immunocyte infiltration, tumor stage, and postoperative recurrence.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: World J Clin Oncol Year: 2024 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: World J Clin Oncol Year: 2024 Document type: Article Affiliation country: China